Business Intelligence & Data Analytics
Identify Untapped Sources of Value

Patient Longitudinal Data Analysis

Patient longitudinal data from claims databases provide a lot of valuable insights on patient behaviour and treatment algorithms being followed in practice.



Persistence Curve

Patient Distribution

Source of Business


The Challenge:

There are quite a few questions that need to be answered after the huge volume of patient data is extracted:

  • What do we want to understand? Is it switches, source of business, patient share, persistence, or compliance?
  • What range of date is applicable to understand current market situation?
  • What are the key assumptions that need to be made and what are the key caveats that one needs to keep in mind while doing this analysis?
Our Deliverable:

Value Edge has developed a SAS based math engine to summarize and calculate the various parameters on the patient longitudinal data such as duration of brand therapy, duration of class therapy, individual patient compliance at individual drug level, use of drug in various line of therapy taking in consideration the various dosing regimen of the individual drug classes. Value Edge's proprietary solution, Patient Edge provides the necessary answers to all questions.

Ad-Hoc Modeling

Value Edge's team takes a very pragmatic approach to do ad-hoc modeling in MS Excel, VBA, Access to offer business solutions to clients. Our clients often have need to build quick tools to do some data management or analytics that does not fall under a specific service line. One example of such a deliverable is given below:


pharma competitive intelligence, biological data analysis, sales volume forecasts in pharma
pharma competitive intelligence, biological data analysis, sales volume forecasts in pharma
pharma business solutions, pharma sales and marketing analytics


The Challenge:

Our client wanted to do a pharmacy stock planning for their key products. The primary questions were:

  • Which are the most important pharmacies where stocking needs to be done on priority?
  • Can we categorize these pharmacies in deciles of priority?
  • What is the quantity of stocking and supply that would be required for the pharmacies?
  • What does that mean for the client in terms of planning distribution to regional distributors?
Our Deliverable:

Value Edge developed an access based tool to do the pharmacy stock planning. The model enabled the client to produce account-specific and targeted stocking recommendations for key trade channel customers, which align with the business dynamics and geographic distribution of retail outlets.


Model and Data Filters

The Launch Stock Plan model provided account-specific stocking recommendations based on data filters that provide a significant level of specificity as to early Rx volume and stocking requirements. Filters employed geographic overlay filters including:

  1. Target physicians
  2. Target patient population
  3. Manufacturer sales representative
  4. Analogue Rx volume movement within retail pharmacy outlets


Output for Trade Channel Accounts

The model produced reports that the client provided to their retail accounts to map out sales volume forecasts and stocking volume.